The TensorFlow Evaluator processor can evaluate each record or evaluate the entire
batch at once.
Configure the
processor to use one of the following evaluation methods, based on the input that the
tensor expects:
- Evaluate each record
- If the tensor requires one input to produce one output, configure the TensorFlow
Evaluator processor to evaluate each record. By default, the processor evaluates
each record, producing one output per record.
-
The processor receives each record as one input, performs the tensor
computations to predict or classify the data, and then produces one output.
The output includes all original fields in the record plus an additional
output field that includes the prediction or classification result. The
output field is a map or list field containing a field for each output that
you configure for the processor.
To evaluate each record, ensure that the following processor properties are
cleared:
- On the General tab, clear the
Produce Events property.
- On the TensorFlow tab, clear the
Entire Batch property.
- Evaluate the entire batch
- If the tensor requires multiple inputs to produce one output, configure the
TensorFlow Evaluator processor to evaluate the entire batch.
- When evaluating a batch, the processor waits until it receives all records in
the batch, performs the tensor computations to predict or classify the data, and
then produces one output as an event for the entire batch. The processor output
includes the original fields in each record. The event output includes the
prediction or classification result.
- To evaluate the entire batch, ensure that the following processor properties are
selected:
- On the General tab, select the Produce
Events property.
- On the TensorFlow tab, select the Entire
Batch property.
- Then, connect the event stream from the TensorFlow Evaluator processor to a
destination to store the prediction or classification result, as described in
Event Generation.
Not valid in Data Collector Edge pipelines. Do not use this evaluation method in Data Collector Edge pipelines.